Evidence map›Paper›PMID 31800403›Full record

ArticleAIDS (London, England)2019

The Estimation and Projection Package Age-Sex Model and the r-hybrid model: new tools for estimating HIV incidence trends in sub-Saharan Africa.

Jeffrey W Eaton, Tim Brown, Robert Puckett, Robert Glaubius, Kennedy Mutai, Le Bao, Joshua A Salomon, John Stover, Mary Mahy, Timothy B Hallett

Open access · hybridAbstract read
In one paragraph

Article in AIDS (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 8 institutions in 4 countries.

Jeffrey W EatonMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Tim BrownResearch Program, East-West Center, Honolulu, Hawaii.
Robert PuckettResearch Program, East-West Center, Honolulu, Hawaii.
Robert GlaubiusAvenir Health, Glastonbury, Connecticut, USA.
Kennedy MutaiNational AIDS Control Council, Nairobi, Kenya.
Le BaoDepartment of Statistics, Pennsylvania State University, University Park, Pennsylvania.
Joshua A SalomonDepartment of Medicine, Stanford University School of Medicine, Stanford, USA.
John StoverAvenir Health, Glastonbury, Connecticut, USA.
Mary MahyJoint United Nations Programme on HIV/AIDS (UNAIDS), Geneva, Switzerland.
Timothy B HallettMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Avenir Health · USEast–West Center · USImperial College London · GBJoint United Nations Programme on HIV/AIDS · CHLondon Centre for Neglected Tropical Disease Research · GBNational Aids Control Council · KEPennsylvania State University · USStanford University · US

Funding

Statistical Models for Estimating and Projecting HIV/AIDS EpidemicsR01AI136664 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI BAO, LE · 2017 to 2021
$3.6M
Quantifying Spatial Representativeness and Uncertainty in Antenatal Care Sentinel Surveillance for HIV in Sub-Saharan Africa.R03AI125001 · NIAID · IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE · PI EATON, JEFFREY WILLIAM · 2017 to 2018
$105k
Medical Research Council MR/R015600/1NIAID NIH HHS R01 AI136664NIAID NIH HHS R03 AI125001
6 · The paper itself

Abstract

objectivesImprove models for estimating HIV epidemic trends in sub-Saharan Africa (SSA).

designMathematical epidemic model fit to national HIV survey and ANC sentinel surveillance (ANC-SS) data.

methodsWe modified EPP to incorporate age and sex stratification (EPP-ASM) to more accurately capture the shifting demographics of maturing HIV epidemics. Secondly, we developed a new functional form for the HIV transmission rate, termed 'r-hybrid', which combines a four-parameter logistic function for the initial epidemic growth, peak, and decline followed by a first-order random walk for recent trends after epidemic stabilization. We fitted the r-hybrid model along with previously developed r-spline and r-trend models to HIV prevalence data from household surveys and ANC-SS in 177 regions in 34 SSA countries. We used leave-one-out cross validation with household survey HIV prevalence to compare model predictions.

resultsThe r-hybrid and r-spline models typically provided similar HIV prevalence trends, but sometimes qualitatively different assessments of recent incidence trends because of different structural assumptions about the HIV transmission rate. The r-hybrid model had the lowest average continuous ranked probability score, indicating the best model predictions. Coverage of 95% posterior predictive intervals was 91.5% for the r-hybrid model, versus 87.2 and 85.5% for r-spline and r-trend, respectively.

conclusionThe EPP-ASM and r-hybrid models improve consistency of EPP and Spectrum, improve the epidemiological assumptions underpinning recent HIV incidence estimates, and improve estimates and short-term projections of HIV prevalence trends. Countries that use general population survey and ANC-SS data to estimate HIV epidemic trends should consider using these tools.

Indexed as

EpidemicsModels, TheoreticalSentinel SurveillanceAfrica South of the SaharaFemaleHIV InfectionsHumansIncidenceMalePrevalence

Identifiers

PMID31800403
PMCPMC6919231
OpenAlexW2989230806

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.